Review on Dexterous Hand Technology Empowered by Computer Science: Multidimensional Integration and Innovative Progress

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This review highlights how computer science advances improve dexterous hand robotics, suggesting key integration approaches and challenges.

Dexterous hand technologies exhibit significant potential, especially in performing human-like manipulation tasks in diverse environments.
Key integration involves data-driven control algorithms that significantly enhance real-time adaptability and precision.
This review focuses on intelligent control, sensor fusion, and machine learning to improve robotic hand design and function.
Future research must address challenges such as perception latency and data scarcity, indicating pathways for enhanced robotic capabilities.

Di Li (2025) studied this question.

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This review highlights how computer science advances improve dexterous hand robotics, suggesting key integration approaches and challenges.